metadata dict | text stringlengths 0 40.6M | id stringlengths 14 255 |
|---|---|---|
{
"filename": "json_format.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/protobuf/py2/google/protobuf/json_format.py",
"type": "Python"
} | # Protocol Buffers - Google's data interchange format
# Copyright 2008 Google Inc. All rights reserved.
# https://developers.google.com/protocol-buffers/
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions are
# met:
#
# * Redi... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@protobuf@py2@google@protobuf@json_format.py@.PATH_END.py |
{
"filename": "README.md",
"repo_name": "3fon3fonov/exostriker",
"repo_path": "exostriker_extracted/exostriker-main/README.md",
"type": "Markdown"
} |
**T**ransit and **R**adial velocity **I**nteractive **F**itting tool for **O**rbital analysis and **N**-body simulations: **The Exo-Striker**
<p align="center">
<img width="400" src="./exostriker/source/png/33_striker.png">
</p>
The Exo-Striker analyzes exoplanet orbitals, performs N-body simulations, and models... | 3fon3fonovREPO_NAMEexostrikerPATH_START.@exostriker_extracted@exostriker-main@README.md@.PATH_END.py |
{
"filename": "create-test-files.py",
"repo_name": "ziotom78/dacapo_calibration",
"repo_path": "dacapo_calibration_extracted/dacapo_calibration-master/create-test-files.py",
"type": "Python"
} | #!/usr/bin/env python3
# -*- encoding: utf-8 -*-
'''Create a set of FITS files to be used as test input for the DaCapo
calibration codes.
'''
import logging as log
import os.path
from typing import Any
from astropy.io import fits
import numpy as np
import healpy
import click
from calibrate import get_dipole_temperatu... | ziotom78REPO_NAMEdacapo_calibrationPATH_START.@dacapo_calibration_extracted@dacapo_calibration-master@create-test-files.py@.PATH_END.py |
{
"filename": "_showbackground.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/layout/scene/zaxis/_showbackground.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class ShowbackgroundValidator(_plotly_utils.basevalidators.BooleanValidator):
def __init__(
self, plotly_name="showbackground", parent_name="layout.scene.zaxis", **kwargs
):
super(ShowbackgroundValidator, self).__init__(
plotly_name=plotly_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@layout@scene@zaxis@_showbackground.py@.PATH_END.py |
{
"filename": "add_rtp_process_record.py",
"repo_name": "HERA-Team/hera_mc",
"repo_path": "hera_mc_extracted/hera_mc-main/scripts/add_rtp_process_record.py",
"type": "Python"
} | #! /usr/bin/env python
# -*- mode: python; coding: utf-8 -*-
# Copyright 2019 the HERA Collaboration
# Licensed under the 2-clause BSD license.
"""Add individual processing record to M&C database from RTP."""
import importlib
import warnings
import numpy as np
import pyuvdata
from astropy.time import Time
from pkg_r... | HERA-TeamREPO_NAMEhera_mcPATH_START.@hera_mc_extracted@hera_mc-main@scripts@add_rtp_process_record.py@.PATH_END.py |
{
"filename": "maths_functions.py",
"repo_name": "ejhigson/perfectns",
"repo_path": "perfectns_extracted/perfectns-master/perfectns/maths_functions.py",
"type": "Python"
} | #!/usr/bin/env python
"""
Mathematical functions.
"""
import numpy as np
import scipy
import scipy.stats
import scipy.special
import scipy.misc
import mpmath
def gaussian_r_given_logx(logx, sigma, n_dim):
"""
Returns r coordinate corresponding to logx values for a Gaussian prior with
the specificed stan... | ejhigsonREPO_NAMEperfectnsPATH_START.@perfectns_extracted@perfectns-master@perfectns@maths_functions.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "keras-team/keras",
"repo_path": "keras_extracted/keras-master/keras/api/applications/densenet/__init__.py",
"type": "Python"
} | """DO NOT EDIT.
This file was autogenerated. Do not edit it by hand,
since your modifications would be overwritten.
"""
from keras.src.applications.densenet import DenseNet121
from keras.src.applications.densenet import DenseNet169
from keras.src.applications.densenet import DenseNet201
from keras.src.applications.de... | keras-teamREPO_NAMEkerasPATH_START.@keras_extracted@keras-master@keras@api@applications@densenet@__init__.py@.PATH_END.py |
{
"filename": "make_suzuki_hdf5.py",
"repo_name": "MESAHub/mesa",
"repo_path": "mesa_extracted/mesa-main/data/rates_data/suzuki/make_suzuki_hdf5.py",
"type": "Python"
} | #!/usr/bin/python
import io
import lzma
import re
import string
import h5py
import numpy as np
def make_mesa_rxn_id(isos, wk_str):
mesa_isos = []
for iso in isos:
m = re.match('(?P<A>[0-9]{1,3})(?P<Z>[A-Z][a-z]?)', iso)
mesa_isos.append('{Z}{A}'.format(**m.groupdict()).lower())
return '_... | MESAHubREPO_NAMEmesaPATH_START.@mesa_extracted@mesa-main@data@rates_data@suzuki@make_suzuki_hdf5.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "icecube/toise",
"repo_path": "toise_extracted/toise-main/toise/figures/diffuse/__init__.py",
"type": "Python"
} | icecubeREPO_NAMEtoisePATH_START.@toise_extracted@toise-main@toise@figures@diffuse@__init__.py@.PATH_END.py | |
{
"filename": "stream_multiline_model.ipynb",
"repo_name": "tere-valdivia/Barnard_5_infall",
"repo_path": "Barnard_5_infall_extracted/Barnard_5_infall-main/B5_IRS1_ALMA/gaussfit_H2CO/analysis_central_chans_masked/stream_multiline_model.ipynb",
"type": "Jupyter Notebook"
} | # Streamline model: calculation of several streamline models at the same time
The idea is to test if a family of streamline model solutions can fit the profile we see, instead of showing only one solution.
## Preliminaries
```python
import numpy as np
import astropy.units as u
from astropy.io import fits
from astro... | tere-valdiviaREPO_NAMEBarnard_5_infallPATH_START.@Barnard_5_infall_extracted@Barnard_5_infall-main@B5_IRS1_ALMA@gaussfit_H2CO@analysis_central_chans_masked@stream_multiline_model.ipynb@.PATH_END.py |
{
"filename": "test_separations.py",
"repo_name": "Jammy2211/PyAutoLens",
"repo_path": "PyAutoLens_extracted/PyAutoLens-main/test_autolens/point/fit/positions/source/test_separations.py",
"type": "Python"
} | import pytest
import autolens as al
def test__two_sets_of_positions__residuals_likelihood_correct():
point_source = al.ps.Point(centre=(0.0, 0.0))
galaxy_point_source = al.Galaxy(redshift=1.0, point_0=point_source)
tracer = al.Tracer(galaxies=[al.Galaxy(redshift=0.5), galaxy_point_source])
positions... | Jammy2211REPO_NAMEPyAutoLensPATH_START.@PyAutoLens_extracted@PyAutoLens-main@test_autolens@point@fit@positions@source@test_separations.py@.PATH_END.py |
{
"filename": "Single_processing.py",
"repo_name": "Wang-Ruihui/A-live-homogeneous-database-of-solar-active-regions",
"repo_path": "A-live-homogeneous-database-of-solar-active-regions_extracted/A-live-homogeneous-database-of-solar-active-regions-main/Single_processing.py",
"type": "Python"
} | # -*- coding: utf-8 -*-
"""
process the single magnetogram
"""
import numpy as np
import matplotlib.pyplot as plt
from astropy.io import fits
from ARdetection import ARdetection, imshow
from ARparameters import ARArea, ARFlux, ARLocat, Distance
# -------------------------------------------------------------------------... | Wang-RuihuiREPO_NAMEA-live-homogeneous-database-of-solar-active-regionsPATH_START.@A-live-homogeneous-database-of-solar-active-regions_extracted@A-live-homogeneous-database-of-solar-active-regions-main@Single_processing.py@.PATH_END.py |
{
"filename": "get_surrogate_model.py",
"repo_name": "psheehan/pdspy",
"repo_path": "pdspy_extracted/pdspy-master/pdspy/modeling/get_surrogate_model.py",
"type": "Python"
} | import schwimmbad
import pickle
import numpy
import time
import os
def get_surrogate_model(params, model="pringle+ulrich+diana", \
quantity="temperature", nthreads=1):
# Load the keys for the parameters of the surrogate model.
keys = list(numpy.loadtxt(os.path.dirname(os.path.abspath(__file__))+\
... | psheehanREPO_NAMEpdspyPATH_START.@pdspy_extracted@pdspy-master@pdspy@modeling@get_surrogate_model.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "amusecode/amuse",
"repo_path": "amuse_extracted/amuse-main/src/amuse/community/mi6/__init__.py",
"type": "Python"
} | from .interface import Mi6
| amusecodeREPO_NAMEamusePATH_START.@amuse_extracted@amuse-main@src@amuse@community@mi6@__init__.py@.PATH_END.py |
{
"filename": "trt_plugin_test.py",
"repo_name": "triton-inference-server/server",
"repo_path": "server_extracted/server-main/qa/L0_trt_plugin/trt_plugin_test.py",
"type": "Python"
} | #!/usr/bin/env python3
# Copyright 2018-2024, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
#
# Redistribution and use in source and binary forms, with or without
# modification, are permitted provided that the following conditions
# are met:
# * Redistributions of source code must retain the above copyright
... | triton-inference-serverREPO_NAMEserverPATH_START.@server_extracted@server-main@qa@L0_trt_plugin@trt_plugin_test.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/matplotlib/py3/matplotlib/__init__.py",
"type": "Python"
} | """
An object-oriented plotting library.
A procedural interface is provided by the companion pyplot module,
which may be imported directly, e.g.::
import matplotlib.pyplot as plt
or using ipython::
ipython
at your terminal, followed by::
In [1]: %matplotlib
In [2]: import matplotlib.pyplot as plt
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@matplotlib@py3@matplotlib@__init__.py@.PATH_END.py |
{
"filename": "bayesian_inference.md",
"repo_name": "renecotyfanboy/jaxspec",
"repo_path": "jaxspec_extracted/jaxspec-main/docs/theory/bayesian_inference.md",
"type": "Markdown"
} | ## A breve introduction to Bayesian philosophy
In a Bayesian inference problem, we gather all the a priori knowledge we have about the problem by defining probability distributions for our parameters $\theta$, the so-called **prior distribution**. We then need to build a statistical model, which will allow us to esti... | renecotyfanboyREPO_NAMEjaxspecPATH_START.@jaxspec_extracted@jaxspec-main@docs@theory@bayesian_inference.md@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/scattersmith/marker/__init__.py",
"type": "Python"
} | import sys
from typing import TYPE_CHECKING
if sys.version_info < (3, 7) or TYPE_CHECKING:
from ._symbolsrc import SymbolsrcValidator
from ._symbol import SymbolValidator
from ._standoffsrc import StandoffsrcValidator
from ._standoff import StandoffValidator
from ._sizesrc import SizesrcValidator
... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@scattersmith@marker@__init__.py@.PATH_END.py |
{
"filename": "sim_wiregrid.py",
"repo_name": "simonsobs/sotodlib",
"repo_path": "sotodlib_extracted/sotodlib-master/sotodlib/toast/ops/sim_wiregrid.py",
"type": "Python"
} | # Copyright (c) 2018-2024 Simons Observatory.
# Full license can be found in the top level "LICENSE" file.
import os
import pickle
import ephem
import h5py
import healpy as hp
import numpy as np
import traitlets
from astropy import constants
from astropy import units as u
from scipy.constants import au as AU
from sci... | simonsobsREPO_NAMEsotodlibPATH_START.@sotodlib_extracted@sotodlib-master@sotodlib@toast@ops@sim_wiregrid.py@.PATH_END.py |
{
"filename": "diagdiag_complex.py",
"repo_name": "ratt-ru/CubiCal",
"repo_path": "CubiCal_extracted/CubiCal-master/cubical/kernels/diagdiag_complex.py",
"type": "Python"
} | # CubiCal: a radio interferometric calibration suite
# (c) 2017 Rhodes University & Jonathan S. Kenyon
# http://github.com/ratt-ru/CubiCal
# This code is distributed under the terms of GPLv2, see LICENSE.md for details
"""
Kernels for 2x2 complex visibilities with diagonal gains. Functions require output arrays to be
... | ratt-ruREPO_NAMECubiCalPATH_START.@CubiCal_extracted@CubiCal-master@cubical@kernels@diagdiag_complex.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "pierfied/karmma",
"repo_path": "karmma_extracted/karmma-master/karmma/__init__.py",
"type": "Python"
} | from .HMCSampler import HMCSampler
from .karmma import KarmmaSampler
from . import utils | pierfiedREPO_NAMEkarmmaPATH_START.@karmma_extracted@karmma-master@karmma@__init__.py@.PATH_END.py |
{
"filename": "triples_integrate.py",
"repo_name": "djmunoz/kozaipy",
"repo_path": "kozaipy_extracted/kozaipy-master/kozaipy/triples_integrate.py",
"type": "Python"
} | import numpy as np
import scipy.integrate as integ
import kozaipy.triples as triples
from .triples_integrate_full import *
from .triples_integrate_tides import *
from .triples_integrate_single_average import *
#import bsint
triple_precision = {"e1x": 1.0e-8,
"e1y": 1.0e-8,
"e1z... | djmunozREPO_NAMEkozaipyPATH_START.@kozaipy_extracted@kozaipy-master@kozaipy@triples_integrate.py@.PATH_END.py |
{
"filename": "paths.py",
"repo_name": "palumbom/sdo-clv-pipeline",
"repo_path": "sdo-clv-pipeline_extracted/sdo-clv-pipeline-main/sdo_clv_pipeline/paths.py",
"type": "Python"
} | from pathlib import Path
# Absolute path to the top level of the repository
root = Path(__file__).resolve().parents[1].absolute()
# Absolute path to the `src` folder
src = root / "sdo_clv_pipeline"
# Absolute path to the `src/data` folder (contains datasets)
data = root / "data"
# Absolute path to the `src/scripts`... | palumbomREPO_NAMEsdo-clv-pipelinePATH_START.@sdo-clv-pipeline_extracted@sdo-clv-pipeline-main@sdo_clv_pipeline@paths.py@.PATH_END.py |
{
"filename": "test_cosmo_sn.py",
"repo_name": "CobayaSampler/cobaya",
"repo_path": "cobaya_extracted/cobaya-master/tests/test_cosmo_sn.py",
"type": "Python"
} | from copy import deepcopy
from .test_cosmo_planck_2015 import params_lowTEB_highTTTEEE
from .common_cosmo import body_of_test
from cobaya.typing import empty_dict
def _test_sn(packages_path, skip_not_installed, lik, theory='camb',
lik_params=empty_dict):
info_likelihood = {lik: lik_params}
info_t... | CobayaSamplerREPO_NAMEcobayaPATH_START.@cobaya_extracted@cobaya-master@tests@test_cosmo_sn.py@.PATH_END.py |
{
"filename": "test_crosscorr.py",
"repo_name": "mlafarga/raccoon",
"repo_path": "raccoon_extracted/raccoon-master/tests/test_crosscorr.py",
"type": "Python"
} | from pathlib import Path
import numpy as np
import pandas as pd
from raccoon import crosscorr
from raccoon import ccflibfort
# Test
def test_get_obj_info():
obj = crosscorr.get_obj_info()
assert obj == 'obj'
# Test funciton runs
def test_ccflibfort_ccfcompute():
w = np.linspace(5000, 5100, 100)
f =... | mlafargaREPO_NAMEraccoonPATH_START.@raccoon_extracted@raccoon-master@tests@test_crosscorr.py@.PATH_END.py |
{
"filename": "_dtickrange.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/histogram2dcontour/colorbar/tickformatstop/_dtickrange.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class DtickrangeValidator(_plotly_utils.basevalidators.InfoArrayValidator):
def __init__(
self,
plotly_name="dtickrange",
parent_name="histogram2dcontour.colorbar.tickformatstop",
**kwargs,
):
super(DtickrangeValidator, self).__init__... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@histogram2dcontour@colorbar@tickformatstop@_dtickrange.py@.PATH_END.py |
{
"filename": "log_gaussian.py",
"repo_name": "rhayes777/PyAutoFit",
"repo_path": "PyAutoFit_extracted/PyAutoFit-main/autofit/mapper/prior/log_gaussian.py",
"type": "Python"
} | from typing import Optional
import numpy as np
from autofit.messages.normal import NormalMessage
from .abstract import Prior
from ...messages.composed_transform import TransformedMessage
from ...messages.transform import log_transform
class LogGaussianPrior(Prior):
__identifier_fields__ = ("lower_limit", "upper... | rhayes777REPO_NAMEPyAutoFitPATH_START.@PyAutoFit_extracted@PyAutoFit-main@autofit@mapper@prior@log_gaussian.py@.PATH_END.py |
{
"filename": "__main__.py",
"repo_name": "nespinoza/juliet",
"repo_path": "juliet_extracted/juliet-master/juliet/__main__.py",
"type": "Python"
} | import sys
def main(args=None):
if args is None:
print('ERROR: You need to pass flags (e.g., -lcfilename, -priorfile, etc.) for juliet to work. \n'+\
' Check out the wiki documentation for a list of flags at https://github.com/nespinoza/juliet/wiki/Installing-and-basic-usage.')
args ... | nespinozaREPO_NAMEjulietPATH_START.@juliet_extracted@juliet-master@juliet@__main__.py@.PATH_END.py |
{
"filename": "line-and-scatter.md",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/doc/python/line-and-scatter.md",
"type": "Markdown"
} | ---
jupyter:
jupytext:
notebook_metadata_filter: all
text_representation:
extension: .md
format_name: markdown
format_version: '1.3'
jupytext_version: 1.16.1
kernelspec:
display_name: Python 3 (ipykernel)
language: python
name: python3
language_info:
codemirror_mode... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@doc@python@line-and-scatter.md@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "nespinoza/transitspectroscopy",
"repo_path": "transitspectroscopy_extracted/transitspectroscopy-master/src/__init__.py",
"type": "Python"
} | from ._version import __version__
__all__ = ['spectroscopy', 'utils', 'transitfitting', 'jwst']
from .spectroscopy import *
from .transitfitting import *
from .utils import *
from .jwst import *
| nespinozaREPO_NAMEtransitspectroscopyPATH_START.@transitspectroscopy_extracted@transitspectroscopy-master@src@__init__.py@.PATH_END.py |
{
"filename": "wd_constants.py",
"repo_name": "Varnani/pywd2015-qt5",
"repo_path": "pywd2015-qt5_extracted/pywd2015-qt5-master/src/helpers/wd_utils/wd_constants.py",
"type": "Python"
} | # a dictionary mapping names to ID's of DC keeps
DC_KEEPS_NAME_ID_DICT = {
"spot_a_lat": 1.0,
"spot_a_long": 2.0,
"spot_a_rad": 3.0,
"spot_a_tempf": 4.0,
"spot_b_lat": 5.0,
"spot_b_long": 6.0,
"spot_b_rad": 7.0,
"spot_b_tempf": 8.0,
"a": 9.0,
"e": 10.0,
"perr": 11.0,
"f... | VarnaniREPO_NAMEpywd2015-qt5PATH_START.@pywd2015-qt5_extracted@pywd2015-qt5-master@src@helpers@wd_utils@wd_constants.py@.PATH_END.py |
{
"filename": "_legendgrouptitle.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/graph_objs/heatmapgl/_legendgrouptitle.py",
"type": "Python"
} | from plotly.basedatatypes import BaseTraceHierarchyType as _BaseTraceHierarchyType
import copy as _copy
class Legendgrouptitle(_BaseTraceHierarchyType):
# class properties
# --------------------
_parent_path_str = "heatmapgl"
_path_str = "heatmapgl.legendgrouptitle"
_valid_props = {"font", "text"... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@graph_objs@heatmapgl@_legendgrouptitle.py@.PATH_END.py |
{
"filename": "_ticklabeloverflow.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/choroplethmapbox/colorbar/_ticklabeloverflow.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class TicklabeloverflowValidator(_plotly_utils.basevalidators.EnumeratedValidator):
def __init__(
self,
plotly_name="ticklabeloverflow",
parent_name="choroplethmapbox.colorbar",
**kwargs,
):
super(TicklabeloverflowValidator, self).__i... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@choroplethmapbox@colorbar@_ticklabeloverflow.py@.PATH_END.py |
{
"filename": "gen_java.py",
"repo_name": "itseez/opencv",
"repo_path": "opencv_extracted/opencv-master/modules/java/generator/gen_java.py",
"type": "Python"
} | #!/usr/bin/env python
import sys, re, os.path, errno, fnmatch
import json
import logging
import codecs
from shutil import copyfile
from pprint import pformat
from string import Template
if sys.version_info[0] >= 3:
from io import StringIO
else:
import io
class StringIO(io.StringIO):
def write(self... | itseezREPO_NAMEopencvPATH_START.@opencv_extracted@opencv-master@modules@java@generator@gen_java.py@.PATH_END.py |
{
"filename": "README.md",
"repo_name": "tloredo/CUDAHM",
"repo_path": "CUDAHM_extracted/CUDAHM-master/README.md",
"type": "Markdown"
} | CUDAHM
======
Routines for using CUDA to accelerate Bayesian inference of Hierarchical Models using Markov Chain Monte Carlo with GPUs.
Description
-----------
`CUDAHM` enables one to easily and rapidly construct an MCMC sampler for a three-level hierarchical model, requiring the user to supply only a minimimal amou... | tloredoREPO_NAMECUDAHMPATH_START.@CUDAHM_extracted@CUDAHM-master@README.md@.PATH_END.py |
{
"filename": "periodic_event.py",
"repo_name": "yuliang419/AstroNet-Vetting",
"repo_path": "AstroNet-Vetting_extracted/AstroNet-Vetting-master/light_curve_util/periodic_event.py",
"type": "Python"
} | # Copyright 2018 The TensorFlow Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to ... | yuliang419REPO_NAMEAstroNet-VettingPATH_START.@AstroNet-Vetting_extracted@AstroNet-Vetting-master@light_curve_util@periodic_event.py@.PATH_END.py |
{
"filename": "datasets.py",
"repo_name": "spedas/pyspedas",
"repo_path": "pyspedas_extracted/pyspedas-master/pyspedas/projects/lanl/datasets.py",
"type": "Python"
} | from pyspedas import find_datasets
# This routine was originally in lanl/__init__.py.
def datasets(instrument=None, label=True):
return find_datasets(mission="LANL", instrument=instrument, label=label)
| spedasREPO_NAMEpyspedasPATH_START.@pyspedas_extracted@pyspedas-master@pyspedas@projects@lanl@datasets.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/graph_objs/volume/legendgrouptitle/__init__.py",
"type": "Python"
} | import sys
from typing import TYPE_CHECKING
if sys.version_info < (3, 7) or TYPE_CHECKING:
from ._font import Font
else:
from _plotly_utils.importers import relative_import
__all__, __getattr__, __dir__ = relative_import(__name__, [], ["._font.Font"])
| catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@graph_objs@volume@legendgrouptitle@__init__.py@.PATH_END.py |
{
"filename": "README.md",
"repo_name": "RuiningZHAO/wcpy",
"repo_path": "wcpy_extracted/wcpy-main/README.md",
"type": "Markdown"
} | # wcpy
A UI for wavelength calibration.
## Installation
```
pip install astro-wcpy
```
## Usage
Type `wavelength-calibrator` in command line. | RuiningZHAOREPO_NAMEwcpyPATH_START.@wcpy_extracted@wcpy-main@README.md@.PATH_END.py |
{
"filename": "README.md",
"repo_name": "rat-pac/rat-pac",
"repo_path": "rat-pac_extracted/rat-pac-master/tools/EventManip/README.md",
"type": "Markdown"
} | EventManip
==========
Overview
--------
This event visualizer uses Mathematica to render fancy 3D plots that are easy to
view, rotate, and zoom. It also incorporates a powerful (though low level)
ability to analyze the event tree, i.e. a tree of tracks with the primary
particle track at the top. One can select subt... | rat-pacREPO_NAMErat-pacPATH_START.@rat-pac_extracted@rat-pac-master@tools@EventManip@README.md@.PATH_END.py |
{
"filename": "paper.md",
"repo_name": "htjb/maxsmooth",
"repo_path": "maxsmooth_extracted/maxsmooth-master/paper/paper.md",
"type": "Markdown"
} | ---
title: 'maxsmooth: Derivative Constrained Function Fitting'
tags:
- Python
- astrophysics
- cosmology
authors:
- name: Harry T. J. Bevins
orcid: 0000-0002-4367-3550
affiliation: "1"
affiliations:
- name: Astrophysics Group, Cavendish Laboratory, J.J.Thomson Avenue, Cambridge, CB3 0HE, United Kingdo... | htjbREPO_NAMEmaxsmoothPATH_START.@maxsmooth_extracted@maxsmooth-master@paper@paper.md@.PATH_END.py |
{
"filename": "test_sdss.py",
"repo_name": "segasai/rvspecfit",
"repo_path": "rvspecfit_extracted/rvspecfit-master/tests/test_sdss.py",
"type": "Python"
} | import os
os.environ['OMP_NUM_THREADS'] = '1'
import astropy.io.fits as pyfits
import numpy as np
import sys
import time
import pathlib
import matplotlib
matplotlib.use('Agg')
import matplotlib.pyplot as plt
from rvspecfit import spec_fit
from rvspecfit import vel_fit
from rvspecfit import utils
path = str(pathlib.P... | segasaiREPO_NAMErvspecfitPATH_START.@rvspecfit_extracted@rvspecfit-master@tests@test_sdss.py@.PATH_END.py |
{
"filename": "CatboostModelAPI.md",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/catboost/CatboostModelAPI.md",
"type": "Markdown"
} | If you want to use a trained model, we provide 4 different ways to do this: C++ while building with ya.make, Python API, dynamic C library with C++ wrapper and C++ header-only evaluator.
## ya.make based projects
If you use `ya.make` build system, the most convenient interface for model evaluation is ```TFullModel``` ... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@catboost@CatboostModelAPI.md@.PATH_END.py |
{
"filename": "test_NIRCam.py",
"repo_name": "kevin218/Eureka",
"repo_path": "Eureka_extracted/Eureka-main/tests/test_NIRCam.py",
"type": "Python"
} | # Last Updated: 2024-02-15
import sys
import os
from importlib import reload
import time as time_pkg
import numpy as np
sys.path.insert(0, '..'+os.sep+'src'+os.sep)
from eureka.lib.readECF import MetaClass
from eureka.lib.util import COMMON_IMPORTS, pathdirectory
import eureka.lib.plots
# try:
# from eureka.S2_c... | kevin218REPO_NAMEEurekaPATH_START.@Eureka_extracted@Eureka-main@tests@test_NIRCam.py@.PATH_END.py |
{
"filename": "rwkv.py",
"repo_name": "langchain-ai/langchain",
"repo_path": "langchain_extracted/langchain-master/libs/community/langchain_community/llms/rwkv.py",
"type": "Python"
} | """RWKV models.
Based on https://github.com/saharNooby/rwkv.cpp/blob/master/rwkv/chat_with_bot.py
https://github.com/BlinkDL/ChatRWKV/blob/main/v2/chat.py
"""
from typing import Any, Dict, List, Mapping, Optional, Set
from langchain_core.callbacks import CallbackManagerForLLMRun
from langchain_core.language... | langchain-aiREPO_NAMElangchainPATH_START.@langchain_extracted@langchain-master@libs@community@langchain_community@llms@rwkv.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "scikit-image/scikit-image",
"repo_path": "scikit-image_extracted/scikit-image-main/skimage/_vendored/__init__.py",
"type": "Python"
} | scikit-imageREPO_NAMEscikit-imagePATH_START.@scikit-image_extracted@scikit-image-main@skimage@_vendored@__init__.py@.PATH_END.py | |
{
"filename": "visualization.animations.md",
"repo_name": "dmentipl/plonk",
"repo_path": "plonk_extracted/plonk-main/docs/source/api/visualization.animations.md",
"type": "Markdown"
} | # Animation
```{eval-rst}
.. autofunction:: plonk.animate
```
```{eval-rst}
.. autofunction:: plonk.visualize.animation_images
```
```{eval-rst}
.. autofunction:: plonk.visualize.animation_particles
```
```{eval-rst}
.. autofunction:: plonk.visualize.animation_profiles
```
| dmentiplREPO_NAMEplonkPATH_START.@plonk_extracted@plonk-main@docs@source@api@visualization.animations.md@.PATH_END.py |
{
"filename": "multisistests2.ipynb",
"repo_name": "j0r1/GRALE2",
"repo_path": "GRALE2_extracted/GRALE2-master/pygrale/doc/source/_static/multisistests2.ipynb",
"type": "Jupyter Notebook"
} | Figure 2 of [Compound lensing: Einstein Zig-Zags and high multiplicity lensed images](http://adsabs.harvard.edu/abs/2016MNRAS.456.2210C)
```python
# This example is very similar to the first notebook in this series.
%matplotlib inline
import grale.plotutil as plotutil
import grale.lenses as lenses
import grale.feedb... | j0r1REPO_NAMEGRALE2PATH_START.@GRALE2_extracted@GRALE2-master@pygrale@doc@source@_static@multisistests2.ipynb@.PATH_END.py |
{
"filename": "mk_package.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/catboost/R-package/mk_package.py",
"type": "Python"
} | from __future__ import print_function
import argparse
import os
import re
import shutil
import subprocess as sp
import sys
import tempfile
def _execute(cmd, **kwargs):
print('{}> {}'.format(os.getcwd(), ' '.join(cmd)))
if kwargs:
assert 0 == sp.check_call(cmd, **kwargs)
else:
assert 0 == s... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@catboost@R-package@mk_package.py@.PATH_END.py |
{
"filename": "_showexponent.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/choropleth/colorbar/_showexponent.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class ShowexponentValidator(_plotly_utils.basevalidators.EnumeratedValidator):
def __init__(
self, plotly_name="showexponent", parent_name="choropleth.colorbar", **kwargs
):
super(ShowexponentValidator, self).__init__(
plotly_name=plotly_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@choropleth@colorbar@_showexponent.py@.PATH_END.py |
{
"filename": "Hitran_data.py",
"repo_name": "spexod/iSLAT",
"repo_path": "iSLAT_extracted/iSLAT-master/iSLAT/COMPONENTS/Hitran_data.py",
"type": "Python"
} | from astroquery import hitran
import pandas as pd
import urllib.request
import ssl
from COMPONENTS.hitran_utils import get_molecule_identifier
from COMPONENTS.global_identifier import get_global_identifier
from astropy import units as un
context = ssl.create_default_context()
context.check_hostname = False
context.ver... | spexodREPO_NAMEiSLATPATH_START.@iSLAT_extracted@iSLAT-master@iSLAT@COMPONENTS@Hitran_data.py@.PATH_END.py |
{
"filename": "PlotSeparation_single.py",
"repo_name": "bradkav/BlackHolesDarkDress",
"repo_path": "BlackHolesDarkDress_extracted/BlackHolesDarkDress-master/Nbody/PlotSeparation_single.py",
"type": "Python"
} | from __future__ import division
from pygadgetreader import *
import matplotlib as mpl
import matplotlib.pyplot as pl
import numpy as np
#----- MATPLOTLIB paramaters ---------
mpl.rcParams.update({'font.size': 12,'font.family':'serif'})
mpl.rcParams['xtick.major.size'] = 7
mpl.rcParams['xtick.major.width'] = 1
mpl... | bradkavREPO_NAMEBlackHolesDarkDressPATH_START.@BlackHolesDarkDress_extracted@BlackHolesDarkDress-master@Nbody@PlotSeparation_single.py@.PATH_END.py |
{
"filename": "rfimitigator.py",
"repo_name": "mtlam/PyPulse",
"repo_path": "PyPulse_extracted/PyPulse-master/pypulse/rfimitigator.py",
"type": "Python"
} | import sys
import numpy as np
if sys.version_info.major == 2:
fmap = map
elif sys.version_info.major == 3:
fmap = lambda x, *args: list(map(x, *args))
xrange = range
class RFIMitigator(object):
def __init__(self, archive):
self.archive = archive
def can_mitigate(self, flag='F'):
''... | mtlamREPO_NAMEPyPulsePATH_START.@PyPulse_extracted@PyPulse-master@pypulse@rfimitigator.py@.PATH_END.py |
{
"filename": "manga_axisym_recover.py",
"repo_name": "kbwestfall/NIRVANA",
"repo_path": "NIRVANA_extracted/NIRVANA-master/nirvana/scripts/manga_axisym_recover.py",
"type": "Python"
} | """
Script that runs the axisymmetric, least-squares fit for MaNGA data.
"""
import os
import argparse
import pathlib
from IPython import embed
import numpy as np
from scipy import sparse
from matplotlib import pyplot
from astropy.io import fits
from ..data import manga
from ..data.bin2d import Bin2D, VoronoiBinnin... | kbwestfallREPO_NAMENIRVANAPATH_START.@NIRVANA_extracted@NIRVANA-master@nirvana@scripts@manga_axisym_recover.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "RobertJaro/InstrumentToInstrument",
"repo_path": "InstrumentToInstrument_extracted/InstrumentToInstrument-master/itipy/download/__init__.py",
"type": "Python"
} | RobertJaroREPO_NAMEInstrumentToInstrumentPATH_START.@InstrumentToInstrument_extracted@InstrumentToInstrument-master@itipy@download@__init__.py@.PATH_END.py | |
{
"filename": "_csrc.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/scatterternary/_csrc.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class CsrcValidator(_plotly_utils.basevalidators.SrcValidator):
def __init__(self, plotly_name="csrc", parent_name="scatterternary", **kwargs):
super(CsrcValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
edi... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@scatterternary@_csrc.py@.PATH_END.py |
{
"filename": "mpl_palette.ipynb",
"repo_name": "mwaskom/seaborn",
"repo_path": "seaborn_extracted/seaborn-master/doc/_docstrings/mpl_palette.ipynb",
"type": "Jupyter Notebook"
} | ```python
import seaborn as sns
sns.set_theme()
sns.palettes._patch_colormap_display()
```
Return discrete samples from a continuous matplotlib colormap:
```python
sns.mpl_palette("viridis")
```
Return the continuous colormap instead; note how the extreme values are more intense:
```python
sns.mpl_palette("viridis"... | mwaskomREPO_NAMEseabornPATH_START.@seaborn_extracted@seaborn-master@doc@_docstrings@mpl_palette.ipynb@.PATH_END.py |
{
"filename": "allskyf7.py",
"repo_name": "kapteyn-astro/kapteyn",
"repo_path": "kapteyn_extracted/kapteyn-master/doc/source/EXAMPLES/allskyf7.py",
"type": "Python"
} | from kapteyn import maputils
import numpy
from service import *
fignum = 7
fig = plt.figure(figsize=figsize)
frame = fig.add_axes(plotbox)
t1 = r"""Slant orthograpic projection (SIN) with: """
t2 = r"""$\xi=\frac{-1}{\sqrt{6}}$ and $\eta=\frac{1}{\sqrt{6}}$
(Cal. fig.10b)"""
title = t1 + t2
xi = -1/numpy.sqrt(6); eta... | kapteyn-astroREPO_NAMEkapteynPATH_START.@kapteyn_extracted@kapteyn-master@doc@source@EXAMPLES@allskyf7.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/scipy/py3/scipy/sparse/csgraph/tests/__init__.py",
"type": "Python"
} | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@scipy@py3@scipy@sparse@csgraph@tests@__init__.py@.PATH_END.py | |
{
"filename": "test_draw.py",
"repo_name": "mj-will/nessai",
"repo_path": "nessai_extracted/nessai-main/tests/test_proposal/test_flowproposal/test_base/test_draw.py",
"type": "Python"
} | # -*- coding: utf-8 -*-
"""Tests related to drawing new points from the pool."""
from unittest.mock import MagicMock
import numpy as np
import pytest
from nessai.proposal.flowproposal.base import BaseFlowProposal
def test_draw_populated(proposal):
"""Test the draw method if the proposal is already populated"""... | mj-willREPO_NAMEnessaiPATH_START.@nessai_extracted@nessai-main@tests@test_proposal@test_flowproposal@test_base@test_draw.py@.PATH_END.py |
{
"filename": "bnb.py",
"repo_name": "huggingface/peft",
"repo_path": "peft_extracted/peft-main/src/peft/tuners/ia3/bnb.py",
"type": "Python"
} | # Copyright 2023-present the HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or... | huggingfaceREPO_NAMEpeftPATH_START.@peft_extracted@peft-main@src@peft@tuners@ia3@bnb.py@.PATH_END.py |
{
"filename": "gaussian_process.py",
"repo_name": "temuller/piscola",
"repo_path": "piscola_extracted/piscola-master/src/piscola/gaussian_process.py",
"type": "Python"
} | import jax
import jaxopt
import numpy as np
import jax.numpy as jnp
from tinygp import GaussianProcess, kernels, transforms
jax.config.update("jax_enable_x64", True)
def prepare_gp_inputs(times, wavelengths, fluxes, flux_errors, fit_log, wave_log):
"""Prepares the inputs for the Gaussian Process model fitting.
... | temullerREPO_NAMEpiscolaPATH_START.@piscola_extracted@piscola-master@src@piscola@gaussian_process.py@.PATH_END.py |
{
"filename": "test_blackbody_with_atm.py",
"repo_name": "mwvgroup/pwv_kpno",
"repo_path": "pwv_kpno_extracted/pwv_kpno-master/tests/test_blackbody_with_atm.py",
"type": "Python"
} | #!/usr/bin/env python3
# -*- coding: UTF-8 -*-
# This file is part of the pwv_kpno software package.
#
# The pwv_kpno package is free software: you can redistribute it and/or
# modify it under the terms of the GNU General Public License as published
# by the Free Software Foundation, either version 3 of th... | mwvgroupREPO_NAMEpwv_kpnoPATH_START.@pwv_kpno_extracted@pwv_kpno-master@tests@test_blackbody_with_atm.py@.PATH_END.py |
{
"filename": "masses.py",
"repo_name": "LoganAMorrison/Hazma",
"repo_path": "Hazma_extracted/Hazma-master/test/vector_mediator/herwig4dm/masses.py",
"type": "Python"
} | from hazma.parameters import (
neutral_pion_mass as __mpi0,
charged_pion_mass as __mpi,
charged_kaon_mass as __mk,
neutral_kaon_mass as __mk0,
eta_mass as __meta,
eta_prime_mass as __metap,
omega_mass as __momega,
fpi as __fpi,
)
mpi0 = __mpi0 * 1e-3
mpi = __mpi * 1e-3
mk = __mk * 1e-3
... | LoganAMorrisonREPO_NAMEHazmaPATH_START.@Hazma_extracted@Hazma-master@test@vector_mediator@herwig4dm@masses.py@.PATH_END.py |
{
"filename": "_hash.py",
"repo_name": "scikit-learn/scikit-learn",
"repo_path": "scikit-learn_extracted/scikit-learn-main/sklearn/feature_extraction/_hash.py",
"type": "Python"
} | # Authors: The scikit-learn developers
# SPDX-License-Identifier: BSD-3-Clause
from itertools import chain
from numbers import Integral
import numpy as np
import scipy.sparse as sp
from sklearn.utils import metadata_routing
from ..base import BaseEstimator, TransformerMixin, _fit_context
from ..utils._param_validat... | scikit-learnREPO_NAMEscikit-learnPATH_START.@scikit-learn_extracted@scikit-learn-main@sklearn@feature_extraction@_hash.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "mikecokina/elisa",
"repo_path": "elisa_extracted/elisa-master/src/elisa/tensor/__init__.py",
"type": "Python"
} | mikecokinaREPO_NAMEelisaPATH_START.@elisa_extracted@elisa-master@src@elisa@tensor@__init__.py@.PATH_END.py | |
{
"filename": "sandbox.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/setuptools/py3/setuptools/sandbox.py",
"type": "Python"
} | from __future__ import annotations
import os
import sys
import tempfile
import operator
import functools
import itertools
import re
import contextlib
import pickle
import textwrap
import builtins
import pkg_resources
from distutils.errors import DistutilsError
from pkg_resources import working_set
if sys.platform.st... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@setuptools@py3@setuptools@sandbox.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "rhayes777/PyAutoFit",
"repo_path": "PyAutoFit_extracted/PyAutoFit-main/autofit/non_linear/samples/__init__.py",
"type": "Python"
} | from .mcmc import SamplesMCMC
from .nest import SamplesNest
from .samples import Samples
from .pdf import SamplesPDF
from .sample import Sample, load_from_table
from .stored import SamplesStored
| rhayes777REPO_NAMEPyAutoFitPATH_START.@PyAutoFit_extracted@PyAutoFit-main@autofit@non_linear@samples@__init__.py@.PATH_END.py |
{
"filename": "check_PPF_approx.ipynb",
"repo_name": "classULDM/class.SFDM",
"repo_path": "class.SFDM_extracted/class.SFDM-master/notebooks/check_PPF_approx.ipynb",
"type": "Jupyter Notebook"
} | ```python
%matplotlib inline
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
from classy import Class
```
```python
k_out = [5e-5, 5e-4, 5e-3]
models = ['PPF1','PPF2','FLD1','FLD1S']
w0 = {'PPF1':-0.7,'PPF2':-1.15,'FLD1':-0.7,'FLD1S':-0.7}
wa = {'PPF1':0.,'PPF2':0.5,'FLD1':0.,'FLD1S':0.}
omega_cd... | classULDMREPO_NAMEclass.SFDMPATH_START.@class.SFDM_extracted@class.SFDM-master@notebooks@check_PPF_approx.ipynb@.PATH_END.py |
{
"filename": "test_source_identifier_extract.py",
"repo_name": "spacetelescope/jdaviz",
"repo_path": "jdaviz_extracted/jdaviz-main/jdaviz/configs/mosviz/tests/test_source_identifier_extract.py",
"type": "Python"
} | from astropy.io.fits import PrimaryHDU
from ..plugins.parsers import _get_source_identifiers_by_hdu, FALLBACK_NAME
def test_SOURCEID():
hdu = PrimaryHDU()
hdu.header['SOURCEID'] = 'Target 1 SOURCEID'
assert _get_source_identifiers_by_hdu([hdu]) == ['Target 1 SOURCEID']
hdu2 = PrimaryHDU()
hdu2.he... | spacetelescopeREPO_NAMEjdavizPATH_START.@jdaviz_extracted@jdaviz-main@jdaviz@configs@mosviz@tests@test_source_identifier_extract.py@.PATH_END.py |
{
"filename": "pops.ipynb",
"repo_name": "ArtificialStellarPopulations/ArtPop",
"repo_path": "ArtPop_extracted/ArtPop-main/docs/tutorials/pops.ipynb",
"type": "Jupyter Notebook"
} | # Building Stellar Populations
[](https://colab.research.google.com/github/ArtificialStellarPopulations/ArtPop/blob/main/colab_tutorials/pops.ipynb)
In this tutorial, we demonstrate **ArtPop**’s built-in stellar population synthesis capability.... | ArtificialStellarPopulationsREPO_NAMEArtPopPATH_START.@ArtPop_extracted@ArtPop-main@docs@tutorials@pops.ipynb@.PATH_END.py |
{
"filename": "errors.md",
"repo_name": "ultralytics/ultralytics",
"repo_path": "ultralytics_extracted/ultralytics-main/docs/en/reference/utils/errors.md",
"type": "Markdown"
} | ---
description: Explore error handling for Ultralytics YOLO. Learn about custom exceptions like HUBModelError to manage model fetching issues effectively.
keywords: Ultralytics, YOLO, error handling, HUBModelError, model fetching, custom exceptions, Python
---
# Reference for `ultralytics/utils/errors.py`
!!! note
... | ultralyticsREPO_NAMEultralyticsPATH_START.@ultralytics_extracted@ultralytics-main@docs@en@reference@utils@errors.md@.PATH_END.py |
{
"filename": "utils_seismic.py",
"repo_name": "BASTAcode/BASTA",
"repo_path": "BASTA_extracted/BASTA-main/src/basta/utils_seismic.py",
"type": "Python"
} | """
Auxiliary functions for frequency analysis
"""
from math import frexp
import os
from copy import deepcopy
from tqdm import tqdm
import numpy as np
from scipy.interpolate import CubicSpline
from basta import freq_fit
from basta import glitch_fit
from basta import fileio as fio
from basta.constants import sydsun a... | BASTAcodeREPO_NAMEBASTAPATH_START.@BASTA_extracted@BASTA-main@src@basta@utils_seismic.py@.PATH_END.py |
{
"filename": "utils.py",
"repo_name": "kpicteam/kpic_pipeline",
"repo_path": "kpic_pipeline_extracted/kpic_pipeline-main/kpicdrp/utils.py",
"type": "Python"
} | import os
from glob import glob
from copy import copy
import itertools
import numpy as np
from scipy.interpolate import interp1d, InterpolatedUnivariateSpline
import astropy.io.fits as fits
from astropy.coordinates import SkyCoord, EarthLocation
import astropy.units as u
import astropy.time as time
import astropy.io.fi... | kpicteamREPO_NAMEkpic_pipelinePATH_START.@kpic_pipeline_extracted@kpic_pipeline-main@kpicdrp@utils.py@.PATH_END.py |
{
"filename": "test_json.py",
"repo_name": "rhayes777/PyAutoFit",
"repo_path": "PyAutoFit_extracted/PyAutoFit-main/test_autofit/mapper/model/serialise/test_json.py",
"type": "Python"
} | import itertools
import os
from pathlib import Path
import pytest
import json
import autofit as af
from autoconf.dictable import from_dict
@pytest.fixture(name="collection_dict")
def make_collection_dict(model_dict):
return {
"arguments": {"gaussian": model_dict},
"type": "collection",
}
@p... | rhayes777REPO_NAMEPyAutoFitPATH_START.@PyAutoFit_extracted@PyAutoFit-main@test_autofit@mapper@model@serialise@test_json.py@.PATH_END.py |
{
"filename": "test_patch_cgm.py",
"repo_name": "mirochaj/ares",
"repo_path": "ares_extracted/ares-main/tests/broken/test_patch_cgm.py",
"type": "Python"
} | """
test_multi_phase.py
Author: Jordan Mirocha
Affiliation: University of Colorado at Boulder
Created on: Sat Feb 21 11:55:00 MST 2015
Description:
"""
import ares
import numpy as np
import matplotlib.pyplot as pl
pars = \
{
'pop_type': 'galaxy',
'pop_sfrd': 'robertson2015',
'pop_Emin': 13.6,
'pop_Emax': 24.... | mirochajREPO_NAMEaresPATH_START.@ares_extracted@ares-main@tests@broken@test_patch_cgm.py@.PATH_END.py |
{
"filename": "_hoverinfo.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py3/plotly/validators/contour/_hoverinfo.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class HoverinfoValidator(_plotly_utils.basevalidators.FlaglistValidator):
def __init__(self, plotly_name="hoverinfo", parent_name="contour", **kwargs):
super(HoverinfoValidator, self).__init__(
plotly_name=plotly_name,
parent_name=parent_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py3@plotly@validators@contour@_hoverinfo.py@.PATH_END.py |
{
"filename": "_color.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/bar/hoverlabel/font/_color.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class ColorValidator(_plotly_utils.basevalidators.ColorValidator):
def __init__(
self, plotly_name="color", parent_name="bar.hoverlabel.font", **kwargs
):
super(ColorValidator, self).__init__(
plotly_name=plotly_name,
parent_name=pare... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@bar@hoverlabel@font@_color.py@.PATH_END.py |
{
"filename": "arima111nc_results.py",
"repo_name": "statsmodels/statsmodels",
"repo_path": "statsmodels_extracted/statsmodels-main/statsmodels/tsa/tests/results/arima111nc_results.py",
"type": "Python"
} | import numpy as np
from statsmodels.tools.tools import Bunch
llf = np.array([-243.77512585356])
nobs = np.array([202])
k = np.array([3])
k_exog = np.array([1])
sigma = np.array([.80556855709271])
chi2 = np.array([14938.241729056])
df_model = np.array([2])
k_ar = np.array([1])
k_ma = np.array([1])
params = np... | statsmodelsREPO_NAMEstatsmodelsPATH_START.@statsmodels_extracted@statsmodels-main@statsmodels@tsa@tests@results@arima111nc_results.py@.PATH_END.py |
{
"filename": "test_fit_notebook.py",
"repo_name": "sherpa/sherpa",
"repo_path": "sherpa_extracted/sherpa-main/sherpa/tests/test_fit_notebook.py",
"type": "Python"
} | #
# Copyright (C) 2020, 2021 Smithsonian Astrophysical Observatory
#
#
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation; either version 3 of the License, or
# (at your option) any later versi... | sherpaREPO_NAMEsherpaPATH_START.@sherpa_extracted@sherpa-main@sherpa@tests@test_fit_notebook.py@.PATH_END.py |
{
"filename": "related.py",
"repo_name": "PrefectHQ/prefect",
"repo_path": "prefect_extracted/prefect-main/src/prefect/events/related.py",
"type": "Python"
} | import asyncio
from typing import (
TYPE_CHECKING,
Any,
Awaitable,
Callable,
Dict,
Iterable,
List,
Optional,
Set,
Tuple,
Union,
)
from uuid import UUID
import pendulum
from pendulum.datetime import DateTime
from .schemas.events import RelatedResource
if TYPE_CHECKING:
... | PrefectHQREPO_NAMEprefectPATH_START.@prefect_extracted@prefect-main@src@prefect@events@related.py@.PATH_END.py |
{
"filename": "httpserver.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/tornado/tornado-6/tornado/httpserver.py",
"type": "Python"
} | #
# Copyright 2009 Facebook
#
# Licensed under the Apache License, Version 2.0 (the "License"); you may
# not use this file except in compliance with the License. You may obtain
# a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, s... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@tornado@tornado-6@tornado@httpserver.py@.PATH_END.py |
{
"filename": "vector_rotate.py",
"repo_name": "spedas/pyspedas",
"repo_path": "pyspedas_extracted/pyspedas-master/pyspedas/projects/erg/satellite/erg/common/cotrans/vector_rotate.py",
"type": "Python"
} | import numpy as np
def vector_rotate(x0, y0, z0, nx, ny, nz, theta):
# Prepare sin\cos values for the rotation angle theta.
dtor = np.pi / 180. # deg --> rad
the = theta * dtor
costhe = np.cos(the)
sinthe = np.sin(the)
# for vector x0 (single component)
x0_length = 1
concatenate_ax... | spedasREPO_NAMEpyspedasPATH_START.@pyspedas_extracted@pyspedas-master@pyspedas@projects@erg@satellite@erg@common@cotrans@vector_rotate.py@.PATH_END.py |
{
"filename": "conf.py",
"repo_name": "GeminiDRSoftware/DRAGONS",
"repo_path": "DRAGONS_extracted/DRAGONS-master/geminidr/doc/progmanuals/GMOSDR_ProgManual/conf.py",
"type": "Python"
} | #
# Tutorial Series - NIRI Imaging Data Reduction with DRAGONS documentation build configuration file, created by
# sphinx-quickstart on Mon Aug 13 15:54:35 2018.
#
# This file is execfile()d with the current directory set to its
# containing dir.
#
# Note that not all possible configuration values are present in this
... | GeminiDRSoftwareREPO_NAMEDRAGONSPATH_START.@DRAGONS_extracted@DRAGONS-master@geminidr@doc@progmanuals@GMOSDR_ProgManual@conf.py@.PATH_END.py |
{
"filename": "test_agreement.py",
"repo_name": "statsmodels/statsmodels",
"repo_path": "statsmodels_extracted/statsmodels-main/statsmodels/graphics/tests/test_agreement.py",
"type": "Python"
} | import numpy as np
import pandas as pd
import pytest
from statsmodels.graphics.agreement import mean_diff_plot
try:
import matplotlib.pyplot as plt
except ImportError:
pass
@pytest.mark.matplotlib
def test_mean_diff_plot(close_figures):
# Seed the random number generator.
# This ensures that the re... | statsmodelsREPO_NAMEstatsmodelsPATH_START.@statsmodels_extracted@statsmodels-main@statsmodels@graphics@tests@test_agreement.py@.PATH_END.py |
{
"filename": "collect_rawproto.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/build/scripts/collect_rawproto.py",
"type": "Python"
} | import argparse
import os
import tarfile
import stat
import sys
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument('--output', required=True)
parser.add_argument('args', nargs='*')
return parser.parse_args()
def main(args):
rawprotos = args.args
with tarfile.open(args.o... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@build@scripts@collect_rawproto.py@.PATH_END.py |
{
"filename": "bispect.py",
"repo_name": "SAIL-Labs/AMICAL",
"repo_path": "AMICAL_extracted/AMICAL-main/amical/mf_pipeline/bispect.py",
"type": "Python"
} | """
@author: Anthony Soulain (University of Sydney)
-------------------------------------------------------------------------
AMICAL: Aperture Masking Interferometry Calibration and Analysis Library
-------------------------------------------------------------------------
Matched filter sub-pipeline method.
Compute ... | SAIL-LabsREPO_NAMEAMICALPATH_START.@AMICAL_extracted@AMICAL-main@amical@mf_pipeline@bispect.py@.PATH_END.py |
{
"filename": "create_instance_catalog.py",
"repo_name": "LSSTDESC/chroma",
"repo_path": "chroma_extracted/chroma-master/bin/phosim/validate/chromatic_seeing_SED/create_instance_catalog.py",
"type": "Python"
} | import os
import numpy
import scipy.integrate
def AB(wave, flambda, AB_wave):
"""Returns the AB magnitude at `AB_wave` (nm) of spectrum specified by
`wave` (in nm), and `flambda` (in erg/s/cm^2/Ang).
"""
speed_of_light = 2.99792458e18 # units are Angstrom Hz
fNu = flambda * (wave * 10)**2 / speed_... | LSSTDESCREPO_NAMEchromaPATH_START.@chroma_extracted@chroma-master@bin@phosim@validate@chromatic_seeing_SED@create_instance_catalog.py@.PATH_END.py |
{
"filename": "roboconf.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/Pygments/py3/pygments/lexers/roboconf.py",
"type": "Python"
} | """
pygments.lexers.roboconf
~~~~~~~~~~~~~~~~~~~~~~~~
Lexers for Roboconf DSL.
:copyright: Copyright 2006-2024 by the Pygments team, see AUTHORS.
:license: BSD, see LICENSE for details.
"""
from pygments.lexer import RegexLexer, words, re
from pygments.token import Text, Operator, Keyword, Name, ... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@Pygments@py3@pygments@lexers@roboconf.py@.PATH_END.py |
{
"filename": "_astropy_init.py",
"repo_name": "NASA-Planetary-Science/sbpy",
"repo_path": "sbpy_extracted/sbpy-main/sbpy/_astropy_init.py",
"type": "Python"
} | # Licensed under a 3-clause BSD style license - see LICENSE.rst
import os
__all__ = ['__version__', 'test']
try:
from .version import version as __version__
except ImportError:
__version__ = ''
# Create the test function for self test
from astropy.tests.runner import TestRunner
test = TestRunner.make_test_ru... | NASA-Planetary-ScienceREPO_NAMEsbpyPATH_START.@sbpy_extracted@sbpy-main@sbpy@_astropy_init.py@.PATH_END.py |
{
"filename": "_scatterpolargl.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/layout/template/data/_scatterpolargl.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class ScatterpolarglValidator(_plotly_utils.basevalidators.CompoundArrayValidator):
def __init__(
self, plotly_name="scatterpolargl", parent_name="layout.template.data", **kwargs
):
super(ScatterpolarglValidator, self).__init__(
plotly_name=plotl... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@layout@template@data@_scatterpolargl.py@.PATH_END.py |
{
"filename": "_bordercolorsrc.py",
"repo_name": "catboost/catboost",
"repo_path": "catboost_extracted/catboost-master/contrib/python/plotly/py2/plotly/validators/splom/hoverlabel/_bordercolorsrc.py",
"type": "Python"
} | import _plotly_utils.basevalidators
class BordercolorsrcValidator(_plotly_utils.basevalidators.SrcValidator):
def __init__(
self, plotly_name="bordercolorsrc", parent_name="splom.hoverlabel", **kwargs
):
super(BordercolorsrcValidator, self).__init__(
plotly_name=plotly_name,
... | catboostREPO_NAMEcatboostPATH_START.@catboost_extracted@catboost-master@contrib@python@plotly@py2@plotly@validators@splom@hoverlabel@_bordercolorsrc.py@.PATH_END.py |
{
"filename": "pallas_shape_poly_test.py",
"repo_name": "jax-ml/jax",
"repo_path": "jax_extracted/jax-main/tests/pallas/pallas_shape_poly_test.py",
"type": "Python"
} | # Copyright 2024 The JAX Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in wri... | jax-mlREPO_NAMEjaxPATH_START.@jax_extracted@jax-main@tests@pallas@pallas_shape_poly_test.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "google/jax",
"repo_path": "jax_extracted/jax-main/jax/scipy/optimize/__init__.py",
"type": "Python"
} | # Copyright 2020 The JAX Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# https://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in wri... | googleREPO_NAMEjaxPATH_START.@jax_extracted@jax-main@jax@scipy@optimize@__init__.py@.PATH_END.py |
{
"filename": "adjust_cropping_extents.py",
"repo_name": "enthought/mayavi",
"repo_path": "mayavi_extracted/mayavi-master/examples/mayavi/interactive/adjust_cropping_extents.py",
"type": "Python"
} | """
A custom dialog to adjust the parameters of a GeometryFilter to crop
data points.
This example shows how to use a GeometryFilter to crop data points, but
also how to build a custom dialog to easily set interactively parameters
of a filter, or any other Mayavi object.
The GeometryFilter crops all data within a bou... | enthoughtREPO_NAMEmayaviPATH_START.@mayavi_extracted@mayavi-master@examples@mayavi@interactive@adjust_cropping_extents.py@.PATH_END.py |
{
"filename": "__init__.py",
"repo_name": "plotly/plotly.py",
"repo_path": "plotly.py_extracted/plotly.py-master/packages/python/plotly/plotly/validators/scattermapbox/marker/__init__.py",
"type": "Python"
} | import sys
from typing import TYPE_CHECKING
if sys.version_info < (3, 7) or TYPE_CHECKING:
from ._symbolsrc import SymbolsrcValidator
from ._symbol import SymbolValidator
from ._sizesrc import SizesrcValidator
from ._sizeref import SizerefValidator
from ._sizemode import SizemodeValidator
from ... | plotlyREPO_NAMEplotly.pyPATH_START.@plotly.py_extracted@plotly.py-master@packages@python@plotly@plotly@validators@scattermapbox@marker@__init__.py@.PATH_END.py |
{
"filename": "test_write_to_fil.py",
"repo_name": "ucberkeleyseti/blimpy",
"repo_path": "blimpy_extracted/blimpy-master/tests/test_write_to_fil.py",
"type": "Python"
} | """
Very small module with one test: test_write_to_fil()
"""
import os
import blimpy as bl
from tests.data import voyager_h5
OUTDIR = os.path.dirname(voyager_h5) + "/"
def test_write_to_fil():
""" Load Voyager dataset and test plotting """
a = bl.Waterfall(voyager_h5)
a.write_to_fil(OUTDIR + 'test_out.f... | ucberkeleysetiREPO_NAMEblimpyPATH_START.@blimpy_extracted@blimpy-master@tests@test_write_to_fil.py@.PATH_END.py |
{
"filename": "run_tess_cutouts.py",
"repo_name": "alexbinks/tessilator",
"repo_path": "tessilator_extracted/tessilator-main/tessilator/scripts/run_tess_cutouts.py",
"type": "Python"
} | from tessilator import tessilator
import numpy as np
import logging
def main(args=None):
fluxCon, lcCon, makePlots, fileRef, tFile = tessilator.setup_input_parameters()
periodFile = tessilator.setup_filenames(fileRef)
logging.basicConfig(filename="output.log", level=logging.INFO)
print(f"Reading th... | alexbinksREPO_NAMEtessilatorPATH_START.@tessilator_extracted@tessilator-main@tessilator@scripts@run_tess_cutouts.py@.PATH_END.py |
{
"filename": "test_checkpoint.py",
"repo_name": "LSSTDESC/Imsim",
"repo_path": "Imsim_extracted/Imsim-main/tests/test_checkpoint.py",
"type": "Python"
} | import os
from pathlib import Path
import numpy as np
import hashlib
import logging
import galsim
import time
import logging
import imsim
import fitsio
import shutil
DATA_DIR = Path(__file__).parent / 'data'
# Used below in both test_checkpoint_image and test_checkpoint_flatten
def timeout_one(config, base, value_typ... | LSSTDESCREPO_NAMEImsimPATH_START.@Imsim_extracted@Imsim-main@tests@test_checkpoint.py@.PATH_END.py |
{
"filename": "utils.py",
"repo_name": "SKA-INAF/caesar-mrcnn-tf2",
"repo_path": "caesar-mrcnn-tf2_extracted/caesar-mrcnn-tf2-main/mrcnn/utils.py",
"type": "Python"
} | """
Mask R-CNN
Common utility functions and classes.
Copyright (c) 2017 Matterport, Inc.
Licensed under the MIT License (see LICENSE for details)
Written by Waleed Abdulla
"""
import math
import random
from distutils.version import LooseVersion
import numpy as np
import skimage
import skimage.transform
import tensor... | SKA-INAFREPO_NAMEcaesar-mrcnn-tf2PATH_START.@caesar-mrcnn-tf2_extracted@caesar-mrcnn-tf2-main@mrcnn@utils.py@.PATH_END.py |
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